MIPS XVII brings together an international community of experts including radiologists, pathologists, other image-based clinicians, psychologists, statisticians, physicists, engineers, and computer scientists investigating the extraction of diagnostic information from medical images. The meeting forges research and learning opportunities for new students and young researchers in a dedicated forum unmatched by other meetings. MIPS XVII is being organized by the Medical Image Perception Society (a US-based society) in conjunction with local hosts Mia Markey, PhD (University of Texas Austin) and Tamara Haygood, MD, PhD (University of Texas MD Anderson Cancer Center). It will run July 12-14, 2017 at the Whitehall Hotel Houston located near the University of Texas MD Anderson campus. Nine topic areas have been selected for MIPS XVII, reflecting important dimensions of medical image interpretation. This year?s special focus theme is addressing other image-based specialties outside radiology. Studying how clinicians extract diagnostic information from images identifies the causes of missed diagnoses and ways to eliminate these errors. Careful design and evaluation of imaging systems are critical in view of their enormous costs. With the current emphasis in the practice of medicine on ?meaningful use? and ?accountable care? to improve the quality, safety, and efficiency of care, the role the clinician as decision-maker cannot be ignored. Medical image perception research develops and applies modern methods to the evaluation of observer performance in diagnostic imaging tasks. Understanding basic aspects of the perception of medical images can reduce diagnostic error and improve medical decision-making quality. This grant will support 10 students to attend and present their research at MIPS XVII. To date, 105 students have been awarded scholarships. The primary goal in supporting these students is to create opportunities and offer supportive mentoring at this formative stage in the trainee?s career to enhance their research potential and likelihood of success.